CN113758496A

CN113758496A - Path planning method and device, electronic equipment and storage medium

Info

Publication number: CN113758496A
Application number: CN202111322252.2A
Authority: CN
Inventors: 程盛远
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2021-11-09
Filing date: 2021-11-09
Publication date: 2021-12-07
Anticipated expiration: 2041-11-09
Also published as: CN113758496B

Abstract

The embodiment of the application provides a path planning method, a path planning device, electronic equipment and a storage medium, which can be applied to the fields of maps, traffic and the like. The method comprises the following steps: the method comprises the steps of obtaining a first starting point and a first terminal point input by a target user and a road section heat data set, wherein the road section heat data set comprises M offline road sections, the M offline road sections are generated based on historical route data of the user, and M is a positive integer; determining N first routes with a starting point as a first starting point and an end point as a first end point according to the M offline road sections, wherein N is a positive integer; and determining at least one recommended route of the target user according to the N first routes. Namely, the method and the device determine N first routes with the starting point as the first starting point and the end point as the first end point based on the M offline road sections, and determine at least one recommended route of the target user according to the N first routes, so that all graph nodes are prevented from being traversed, and the route planning efficiency is improved.

Description

Path planning method and device, electronic equipment and storage medium

Technical Field

The embodiment of the application relates to the technical field of intelligent travel, in particular to a path planning method and device, electronic equipment and a storage medium.

Background

With the rapid development of the intelligent travel technology, public transport navigation software is generated randomly. For example, a user enters a start point and an end point on a client of public transportation navigation software that may calculate at least one public transportation path recommendation for the user to the user. The user can determine a travel route and a travel riding public transport means according to the recommended at least one public transport route.

However, the current path planning method has the problem of low path planning efficiency.

Disclosure of Invention

The embodiment of the application provides a path planning method and device, electronic equipment and a storage medium, so as to improve the efficiency of path planning.

In a first aspect, an embodiment of the present application provides a path planning method, including:

acquiring a first starting point and a first terminal point input by a target user and a road section heat data set, wherein the road section heat data set comprises M offline road sections, the M offline road sections are generated based on historical route data of the user, and M is a positive integer;

determining N first routes with the starting points as the first starting points and the end points as the first end points according to the M offline road sections, wherein N is a positive integer;

and determining at least one recommended route of the target user according to the N first routes.

In a second aspect, an embodiment of the present application provides a path planning apparatus, including:

the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a first starting point and a first terminal point input by a target user, and a road section heat data set, the road section heat data set comprises M offline road sections, the M offline road sections are generated based on historical route data of the user, and M is a positive integer;

a first determining unit, configured to determine, according to the M offline road segments, N first routes having a starting point as the first starting point and an end point as the first end point, where N is a positive integer;

and the second determining unit is used for determining at least one recommended route of the target user according to the N first routes.

Optionally, the M offline sections include at least one of an offline express section and an offline transfer section.

In some embodiments, if the M offline road segments include an offline express road segment, the first determining unit is specifically configured to query, in the offline express road segment, a first express route having a start point as the first start point and an end point as the first end point; determining the first direct route as the first route.

In some embodiments, the first determining unit is specifically configured to use P bus stops that are less than a first preset distance from the first start point as P candidate start stations, and use Q bus stops that are less than a second preset distance from the first end point as Q candidate end stations; for the ith candidate starting station in the P candidate starting stations and the jth candidate terminal station in the Q candidate terminal stations, in the offline direct road section, querying a first direct route with a starting point of the ith candidate starting station and a terminal point of the jth candidate terminal station, wherein i is a positive integer from 1 to P, and j is a positive integer from 1 to Q.

In some embodiments, the second determining unit is further configured to calculate, according to a preset path calculation method, a second direct route with a starting point as the first starting point and an end point as the first end point; and determining at least one recommended route of the target user according to the N first routes and the second direct route.

In some embodiments, the second determining unit is specifically configured to select, from the first direct route and the second direct route, at least one third direct route having a direct route from the end point to the start point; and determining at least one recommended route of the target user according to the at least one third direct route.

In some embodiments, the first determining unit is specifically configured to generate, according to the M offline sections, a first transfer route having a starting point as the first starting point and an end point as the first end point; and determining the first transfer route as the first route.

In some embodiments, the first determining unit is specifically configured to, when traversing a current site according to a preset path calculation method, use an offline section corresponding to a sub-site of the current site in the M offline sections as a candidate section of the current site, where the current site is the first starting point or any site; and generating the first transfer route according to the candidate road section of the current station.

In some embodiments, the second determining unit is further configured to calculate a second transfer route, in which a starting point is the first starting point and an end point is the first end point, according to a preset path calculation method; and determining at least one recommended route of the target user according to the N first routes and the second transfer route.

In some embodiments, the M offline sections are sections formed by multi-path splitting of a plurality of offline routes based on a site, the plurality of offline routes being a plurality of routes generated based on a starting point and an ending point in the historical route data of the user.

Optionally, the number of times that the starting point and the end point in the historical route data of the user are visited by the user is greater than a first value.

Optionally, the number of transfers of each offline section in the M offline sections is less than a second numerical value.

In some embodiments, the section heat data set further includes a heat value corresponding to each of the M offline sections, and the second determining unit is specifically configured to determine, for each of the N first routes, a heat value of the first route according to the heat value of the offline section corresponding to the first route; and determining at least one recommended route of the target user according to the corresponding heat value of each route in the N first routes.

In some embodiments, the heat value of the offline section is determined based on at least one of the number of times the offline section is accessed, the distance of the offline section, the total elapsed time corresponding to the offline section, the riding time corresponding to the offline section, the walking time corresponding to the offline section, and the number of transfers corresponding to the offline section.

In a third aspect, a computing device is provided that includes a processor and a memory. The memory is configured to store a computer program, and the processor is configured to call and execute the computer program stored in the memory to perform the method in the first aspect or each implementation manner thereof.

In a fourth aspect, a chip is provided for implementing the method in any one of the first to second aspects or implementations thereof. Specifically, the chip includes: a processor, configured to call and run a computer program from a memory, so that a device on which the chip is installed performs the method according to any one of the above first aspects or the implementation manners thereof.

In a fifth aspect, a computer-readable storage medium is provided for storing a computer program, the computer program causing a computer to perform the method of any one of the above aspects or implementations thereof.

A sixth aspect provides a computer program product comprising computer program instructions for causing a computer to perform the method of any of the above aspects or implementations thereof.

In a seventh aspect, a computer program is provided, which, when run on a computer, causes the computer to perform the method of any one of the above first aspects or implementations thereof.

In summary, the first start point and the first end point input by the target user and the road section heat data set are obtained, wherein the road section heat data set comprises M offline road sections, the M offline road sections are generated based on historical route data of the user, and M is a positive integer; determining N first routes with a starting point as a first starting point and an end point as a first end point according to the M offline road sections, wherein N is a positive integer; and determining at least one recommended route of the target user according to the N first routes. Namely, the method and the device determine N first routes with the starting point as the first starting point and the end point as the first end point based on the M offline road sections, and determine at least one recommended route of the target user according to the N first routes, so that all graph nodes are prevented from being traversed, and the route planning efficiency is improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.

Fig. 1 is a schematic view of an application scenario according to an embodiment of the present application;

FIG. 2 is a directed graph according to an embodiment of the present application;

fig. 3 is a schematic flow chart of a path planning method according to an embodiment of the present application;

FIG. 4 is a schematic node traversal diagram according to an embodiment of the present application;

FIG. 5 is a schematic illustration of a direct route according to an embodiment of the present application;

fig. 6 is a schematic diagram of a candidate initiating station according to an embodiment of the present application;

FIG. 7 is a schematic diagram of transfer route generation according to an embodiment of the present application;

FIG. 8 is a schematic diagram of a transfer route generated using a method of an embodiment of the present application;

fig. 9 is a schematic flowchart of a path planning method according to an embodiment of the present application;

FIG. 10 is a schematic diagram of a proposed route to which the present application relates;

fig. 11 is a schematic structural diagram of a path planning apparatus according to an embodiment of the present application;

fig. 12 is a schematic block diagram of a computing device provided by an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

The embodiment of the application is applied to the technical field of map, traffic and intelligent travel and is used for recommending public travel routes for users.

It should be understood that, in the present embodiment, "B corresponding to a" means that B is associated with a. In one implementation, B may be determined from a. It should also be understood that determining B from a does not mean determining B from a alone, but may be determined from a and/or other information.

In the description of the present application, "plurality" means two or more than two unless otherwise specified.

In addition, in order to facilitate clear description of technical solutions of the embodiments of the present application, in the embodiments of the present application, terms such as "first" and "second" are used to distinguish the same items or similar items having substantially the same functions and actions. Those skilled in the art will appreciate that the terms "first," "second," etc. do not denote any order or quantity, nor do the terms "first," "second," etc. denote any order or importance.

Fig. 1 is a schematic view of an application scenario related to an embodiment of the present application, and as shown in fig. 1, the application scenario includes: a client 101 and a server 102 connected to the client 101.

In some embodiments, the client 101 is installed on a terminal device 103, the terminal device 103 may be a User Equipment (UE), the user terminal may be a wireless terminal device 103 or a wired terminal device, the wireless terminal device may refer to a device having a wireless transceiving function, and the user terminal may be a mobile phone (mobile phone), a tablet computer (Pad), a computer with a wireless transceiving function, a Virtual Reality (VR) user device, an Augmented Reality (AR) user device, and the like, which are not limited herein.

In some embodiments, the server 102 may be one or more. When the number of the servers 102 is multiple, at least two servers 102 exist for providing different services, and/or at least two servers 102 exist for providing the same service, for example, the same service is provided in a load balancing manner, which is not limited in the embodiment of the present application. The server 102 may be provided with a reconstruction model, and the server 102 provides support for the training and application process of the reconstruction model. The server 102 may be an independent physical server 102, a server 102 cluster or a distributed system formed by a plurality of physical servers 102, or a cloud server 102 providing basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a CDN (Content Delivery Network), a big data and artificial intelligence platform, and the like. The server 102 may also become a node of the blockchain.

In actual use, a user inputs a starting point and an end point on the terminal device 103, the terminal device 103 sends the starting point and the end point information to the server 102, and the server 102 generates at least one recommended route for the user according to the method of the embodiment of the application.

It should be noted that the application scenarios in the embodiment of the present application include, but are not limited to, that shown in fig. 1, for example, the terminal device may also execute the public transportation path planning method provided in the embodiment of the present application, and generate at least one recommended route for the user.

The following describes related art to which embodiments of the present application relate.

The path planning service is an online service for providing the optimal riding scheme with preset number for the user according to the starting point and the ending point of the user. For example, bus planning services: inputting and planning the on-line service of the optimal 5 bus transfer schemes according to the starting and ending points, the starting time, the user preference and the like of the user, and ensuring the reasonability and diversity of the schemes.

Directed graph D refers to an ordered triple (V (D), A (D), ψ D), where ψ D is the correlation function that makes each element in A (D) (called directed edge or arc) correspond to an ordered pair of elements in V (D) (called vertex or point). As shown in fig. 2, each bus stop in the present application is a vertex (or node) of a directed graph, and if there is a direct public transportation route between two stops, the two stops are connected to form an edge of the directed graph.

The current path planning method includes a Breadth-First-Search (BFS) algorithm, a Depth-First-Search (DFS) algorithm, an a-star (also referred to as a-star) algorithm, and the like.

BFS, also known as breadth first search. The BFS algorithm is to traverse the nodes of the tree along its width, starting from the root node. If all nodes are visited, the algorithm terminates. The method specifically comprises the following steps:

step 1, firstly, a root node is put into a queue.

And 2, taking out the first node from the queue and checking whether the first node is a target. If the node is the target, the search is finished and the result is returned. If the node is not the target node, the node is removed from the queue, and all direct child nodes which have not been checked by the node are added into the queue.

And 3, next, selecting a new node from the queue as a first node, returning to execute the step 2, and circulating the steps until the queue is empty, which indicates that all the nodes are traversed.

All nodes of the BFS algorithm must be stored, so the spatial complexity of BFS is O (| V | + | E |), where | V | is the number of nodes and | E | is the number of edges in the graph.

In contrast to BFS, DFS first examines all the children of a node, searches for branches of the graph as deeply as possible, and then returns to the layer where the node is located to continue traversing when all the children of the current node are traversed. The whole process is repeated until all nodes are traversed. I.e. starting from the initial node, the expansion order always expands the newly generated node first. This allows the search to proceed along a single path in the state space until the last node fails to generate a new node or a target node is found. When the search result shows that the new node can not be generated, the node which can generate the new node is searched along the reverse direction of the node generation sequence, and the node is expanded to form another search path.

To facilitate the search, a table is provided to store all nodes. In the depth-first search algorithm, the principle of expanding nodes generated first and then expanding is satisfied, so the table of the storage node generally adopts a data structure of a stack.

The search steps of the depth-first search algorithm are generally:

step 1, starting from an initial node, sequentially placing nodes to be expanded into a stack.

And 2, if the stack is empty, namely all the nodes to be expanded are completely expanded, the problem is solved and the operation is exited.

And 3, taking the newly added nodes in the stack, namely the stack top node, popping the stack, expanding all child nodes by using a corresponding expansion principle, and putting the nodes into the stack in sequence. And if no child node is generated, returning to the step 2.

And 4, if a certain child node is a target node, finding a solution of the problem (which is not necessarily the optimal solution), and ending. And if the optimal solution of the problem is required, or all solutions are required, returning to the step 2, and continuously searching for a new target node.

A is a heuristic search, and the search range is reduced by introducing estimated cost, so that the search efficiency is improved. The formula is expressed as: f (n) = g (n) + h (n), where f (n) is the cost estimate from the graph root node to the end point via node n, g (n) is the actual cost from the root node to node n, and h (n) is the estimated cost of the best path from node n to the end point.

From the above, the BFS and DFS can theoretically find a globally optimal path, but there are problems of large search space and low efficiency due to the need to traverse all graph nodes (i.e., sites).

In order to solve the above technical problem, in the embodiments of the present application, a method of offline calculation and online skipping is comprehensively utilized, M offline road segments are mined, N first routes having a starting point as a first starting point and an end point as a first end point are determined based on the M offline road segments during online search, and at least one recommended route of a target user is determined according to the N first routes, so that traversal of all graph nodes is avoided, and further, the efficiency of path planning is improved.

Fig. 3 is a schematic flow chart of a path planning method according to an embodiment of the present application, as shown in fig. 3, including:

s301, acquiring a first starting point and a first ending point input by a target user and a road section heat data set.

The road section heat data set comprises M offline road sections, the M offline road sections are generated based on historical route data of a user, and M is a positive integer.

The execution subject of the embodiment of the present application is a device having a path planning function, for example, a path planning device, where the path trajectory device is a computing device or a processor in the computing device.

In some embodiments, the computing device is a server as described above in connection with the client.

In some embodiments, the computing device is a terminal device on which the client is installed.

Optionally, the computing device may be another computing device connected to the client.

The client can be a navigation client or other clients with a function of providing path planning.

In practical use, a user opens a client installed on a terminal device, and inputs a starting point and an end point on a corresponding page of the client.

The client sends the first start point and the first end point input by the user to a computing device connected with the client, for example, to a server connected with the client. After obtaining the first start point and the first end point input by the user, the computing device executes the method of the embodiment of the application.

Before the embodiment of the application is executed, a road section heat data set is generated in advance, and the road section heat data set comprises M offline road sections.

The method for acquiring the road section heat data set includes, but is not limited to, the following methods:

in a first mode, the computing device of the application generates a road section heat data set according to historical route data of a user and stores the generated road section heat data set. And when a path query request input by a user is received, acquiring the road section heat data set from the storage device.

In a second way, the computing device of the present application obtains the road segment heat data set from other storage devices, for example, when receiving a path query request input by a user, obtains the road segment heat data set from other storage devices, or when the user starts the client, obtains the road segment heat data set from other storage devices. In the second mode, the time for the computing device to read the road segment heat data set is not limited, as long as it is ensured that the road segment heat data set is obtained when the path planning provided by the embodiment of the present application is performed.

The generation process of the section heat data set is described below.

The road section heat data set is generated based on historical route data of a user, and specifically comprises the following steps A and B:

and step A, generating an offline line based on historical route data of a user.

Alternatively, the historical route data of the user may be route data generated by different users in a certain historical time period. Alternatively, the historical route data of the user may be route data generated by the same user, for example, a target user, in a certain historical time period.

In step a, the ways of generating the offline route based on the historical route data of the user include, but are not limited to, the following:

in the first mode, the historical route data includes a start point and an end point input by the user in one path request, and the start point and the end point are called as a start-end point pair. And according to the historical starting and ending point pairs of the users, calculating by using the existing path planning, recalculating the path corresponding to each historical starting and ending point, and obtaining the off-line route.

In some embodiments, the historical route data used in this step may be route data for different users over a historical period of time, the route data including pairs of start and end points for the different users. For example, user a enters 100 pairs of start and end points on a client while using the client during a historical period of time. When the user B uses the client in the historical time period, 200 pairs of starting points and end points are input on the client, and the like, and route data of a plurality of users in the historical time period are obtained.

In some embodiments, the historical data route may be route data of the target user over a historical period of time. For example, when a target user uses a client during a historical time, 1000 pairs of start and end point pairs are entered on the client.

In some embodiments, in order to improve the accuracy of route planning, historical route data of a user is screened, historical route data of which the starting point and the ending point are visited by the user more frequently than a first value are screened out to generate road section popularity data, and then more popular historical route data are selected for route planning, so that the accuracy of route planning is improved. The specific value of the first numerical value is not limited in the present application, for example, the first numerical value is 3, or the first numerical value is 10.

Optionally, before generating the road section heat data set based on the historical route data of the user, coordinate conversion is performed on the coordinates of the historical starting point pair, for example, the geographic coordinates, the mercator coordinates, and the like of the historical starting point pair are uniformly converted into coordinate values in a preset coordinate system. And further generating an off-line route based on the coordinate values of the historical starting point pairs in the preset coordinate system.

In some embodiments, in order to increase the number of the calculated offline routes, the embodiments of the present application may fully utilize the characteristics that the space requirement and the search efficiency are far lower than the online requirements, the threshold value using the conventional algorithm may be set to recall as many routes as possible, and the recall cost and the sorted characteristic value used in the middle may be fully calculated, such as more features are adopted, real services are accessed, and the like.

In one example, offline routes are recalled using the a-algorithm, where the offline routes are recalled using the following equation (1):

f(n) ＝ g(n) + h(n) （1）

wherein g (n) is the generated cost of arriving at the location n, also called the true cost; h (n) is an estimate, also called the estimated cost, from location n to the destination. Alternatively, the estimated cost h (n) may adopt a value of a driving scene, or a time consumption of a walking service, etc.

In another example, when the offline route is recalled using the BFS algorithm, as many nodes are traversed as possible, for example, each node originally limits to traverse 2 child nodes, the present application may be extended to traverse at least 3 child nodes, as shown in fig. 4, the present application may traverse child node 4 of node 1, and further add routes of 1- >4 and 4- > 8. Optionally, the traversal order of each site shown in fig. 4 is 1- >2- >3- >4- >5- >6- >7- >8- >9, and the obtained candidate route segments are 1-4-8, 1-3-7, 1-2-6-9, 1-2-5, and the like.

Then, the heat value of the candidate route segment is determined, and the newly added routes 1- >4- >8 are possibly output as heat segments, so that the number of the off-line routes is increased.

In some embodiments, for each offline route, a heat value of the offline route is determined according to at least one of walking time, riding time, distance, transfer times, etc. from the starting point to the end point of the offline route according to the total time consumption of the offline route. For example, the lower the elapsed time, the less the number of walks, the fewer detours, and the fewer number of transfers under the same conditions, the higher the heat value.

And sorting the calculated off-line routes according to the heat values of the off-line routes, for example, sorting the off-line routes from large to small according to the heat values.

The information used for calculating the heat value includes, but is not limited to, the total time, the walking time from the start point to the end point, the riding time, the distance, the number of transfers, and the like.

In the first mode, route planning is performed according to historical starting and ending points in historical route data to obtain an offline route. The method of the second mode can be adopted to generate the off-line route.

And in the second mode, the historical route data of the user comprises a route recommended by the client for the user in historical time, based on the route recommended by the client, the historical recommended route in the historical route data is extracted, and the historical recommended route is determined as an offline route.

According to the method of the first and second aspects, after the offline route is generated based on the historical route data of the user, the following step B is performed to obtain the offline section.

And step B, performing multi-path section splitting on at least one of the off-line routes based on the station to obtain M route paths.

In other words, in order to meet the situation that the riding section is a part of the sections in the offline route, the offline route is split into multiple sections.

For example, for offline routes a and B calculated in step a above:

an offline route A: 1-3-4-8;

an offline route B: 1-4-8.

And splitting the offline route A and the offline route B according to the station to obtain a plurality of offline sections.

Optionally, the heat value of the offline section may also be determined according to the number of occurrences of the offline section in each offline route. For example, one simple method is to count one minute at a time, before high ranking.

Illustratively, the offline routes a and B are subjected to segment splitting, so as to obtain offline segments as shown in table 1.

TABLE 1

Road section	At route A occurrence of +1	Occurrence of +1 on route B	Heat value
				1-3	1		1
1-3-4	1		1
				1-3-4-8	1		1
3-4	1		1
				3-4-8	1		1
1-4		1	1
				1-4-8		1	1
4-8	1	1	2

Table 1 above determines the heat value of the offline section according to the number of occurrences of the offline section in each offline route.

Optionally, the heat value of each road section can be determined according to the characteristics of the off-line road section, for example, a score higher than that of a common bus section is given to the subway section.

In some embodiments, in addition to determining the heat value of the offline section based on the number of times the offline section is accessed, the heat value of the offline section may be determined according to at least one of a distance of the offline section, a total elapsed time corresponding to the offline section, a riding time corresponding to the offline section, a walking time corresponding to the offline section, and a number of transfers corresponding to the offline section. For example, the shorter the distance of the offline section, the smaller the total time consumption corresponding to the offline section, the smaller the riding time corresponding to the offline section, the smaller the walking time corresponding to the offline section, and the smaller the number of transfers corresponding to the offline section, the higher the heat value of the corresponding offline section.

In some embodiments, the possibility of selecting a route with an excessive number of transfers by a user is low, and therefore, after the offline sections are obtained by splitting according to the method, the offline sections with the number of transfers greater than a preset value (for example, 3 times) are filtered out, so that the amount of unnecessary calculation is reduced.

That is, the number of transfers of each of the M offline sections of the present application is less than the second numerical value. The second value is not limited in size, for example, the second value is 1, 2, 3, etc.

In some embodiments, the M offline sections include at least one of an offline express section and an offline transfer section.

In which the express link is a route that does not require transfer, for example, as shown in fig. 5, from a starting point a1 to an end point B1, the riding route has only one subway 16 line, does not require intermediate transfer, and only may need to walk from the current position (starting point) to the starting point and from the end point to the end point.

When the transfer road section is from the starting point to the end point, the vehicle needs to be transferred at least twice, for example, from the starting point A1 to the end point B2, the bus 6 line needs to be transferred from the starting point A1 to the transfer point C1, and then from the transfer point C1 to the end point B2, the subway 2 line needs to be transferred.

Optionally, the offline transfer road section includes a primary transfer road section, a secondary transfer road section, a multi-transfer road section, and the like.

S302, according to the M offline road sections, determining N first routes with the starting point as a first starting point and the end point as a first end point.

Wherein N is a positive integer.

According to the method and the device, the N first routes with the starting point as the first starting point and the end point as the first end point are determined according to the generated M offline road sections, so that each node in the graph is prevented from being traversed, and the path planning efficiency is improved.

The implementation manners of S302 include, but are not limited to, the following:

in a first mode, in the M offline sections, the offline sections with the starting point as the first starting point and the ending point as the first ending point are searched, and the offline sections are recorded as the first route.

In a second mode, if the M offline road segments include an offline through road segment, the step S302 includes the steps S302-a1 and S302-a 2:

S302-A1, in the offline direct road section, inquiring a first direct route with the starting point as a first starting point and the end point as a first end point;

S302-A2, determining the first arrival route as a first route.

In this embodiment, if the section heat data set includes the offline direct sections, a first start point may be queried from the offline direct sections, and the offline direct section whose end point is the first end point is recorded as the first direct route, and the first direct route is determined as the first route.

The application does not limit the specific implementation manner of the above-mentioned S302-a 1.

In one example, the above S302-a1 includes the following steps:

S302-A11, taking P bus stops which are less than a first preset distance from a first starting point as P candidate starting stations, and taking Q bus stops which are less than a second preset distance from a first terminal point as Q candidate terminal stations;

S302-A12, aiming at the ith candidate starting station in the P candidate starting stations and the jth candidate terminal station in the Q candidate terminal stations, in the offline direct road section, inquiring a first direct route with the starting point being the ith candidate starting station and the terminal point being the jth candidate terminal station, wherein i is a positive integer from 1 to P, and j is a positive integer from 1 to Q.

Optionally, the first start point and the first end point input by the target user are checked, for example, to screen out erroneous input, such as input points without latitude and longitude or input points with invalid latitude and longitude.

Optionally, the coordinate information of the first start point and the first end point is subjected to coordinate conversion, for example, the input geographic coordinate, the input mercator coordinate, and the like are uniformly converted into coordinate values in a preset coordinate system.

In practical application, there may be a plurality of bus stops near the starting point and the ending point, but a user usually selects that the distance from walking to the starting point and the distance from walking to the ending point after getting off are generally shorter, and based on the selection, some stops farther from the starting point and the ending point are filtered out, so that the pressure of subsequent calculation is reduced. For example, P bus stops with a distance from the first starting point smaller than a first preset distance are selected as P candidate starting stations, and Q bus stops with a distance from the first ending point smaller than a second preset distance are selected as Q candidate ending stations.

Optionally, specific values of the first preset distance and the second preset distance are not limited, for example, if the first preset distance and the second preset distance are 1km, P bus stops closest to the first start point within 1km are selected as P candidate start stops, and Q bus stops closest to the first end point within 1km are selected as Q candidate end stops.

Alternatively, the distance between the first start point and the candidate start station may be calculated as a straight line distance, a manhattan distance, or a walking distance, etc.

Illustratively, as shown in fig. 6, there are 6 candidate initiators within the starting point straight line range 1KM, which are the candidate initiator 1, the candidate initiator 2, the candidate initiator 3, the candidate initiator 4, the candidate initiator 5, and the candidate initiator 6, respectively.

Aiming at the ith candidate starting station in the P candidate starting stations and the jth candidate terminal station in the Q candidate terminal stations, in the offline direct road section, a first direct route with the starting point as the ith candidate starting station and the terminal point as the jth candidate terminal station is inquired. For example, both P and Q are 6, and for the first candidate start station, the first candidate start station is used as the start station, the first candidate end station of the Q candidate end stations is used as the end station, the offline direct link section with the first candidate start station as the start station and the first candidate end station as the end station is inquired in the offline direct link section, and the offline direct link section is recorded as the first direct route. Then, the offline direct road section which takes the first candidate starting station as the starting station and takes the second candidate terminal station in the Q candidate terminal stations as the terminal station is inquired in the offline direct road section, the offline direct road section is recorded as a first direct route, the process is repeated until the traversal of the Q and P stations is finished.

In the second mode, if the first direct route with the start point as the first start point and the end point as the first end point exists in the offline direct road section, at least one recommended route can be directly inquired for the target user from the offline direct road section without traversing and searching nodes, and the efficiency of path planning is greatly improved.

In a third mode, if the N first routes include the transfer route, the step S302 includes the steps S302-B1 and S302-B2:

S302-B1, generating a first transfer route with a starting point as the first starting point and an end point as the first end point according to the M offline road sections;

S302-B2, determining the first transfer route as the first route.

The implementation of S302-B1 described above includes but is not limited to the following examples:

example 1, the offline heat data of the present application includes a plurality of offline transfer sections, so that it can be directly queried whether there is a first transfer route having a starting point as a first starting point and an ending point as a first ending point in each offline transfer section.

For example, referring to the above method, P bus stops less than a first preset distance from a first start point are taken as P candidate start stations, and Q bus stops less than a second preset distance from a first end point are taken as Q candidate end stations; for the ith candidate starting station in the P candidate starting stations and the jth candidate terminal station in the Q candidate terminal stations, inquiring a first transfer route with the starting point being the ith candidate starting station and the terminal point being the jth candidate terminal station in the offline transfer section, wherein i is a positive integer from 1 to P, and j is a positive integer from 1 to Q.

Example 2, the above S302-B1 includes the following steps S302-B11 and S302-B12:

S302-B11, when traversing the current site according to a preset path calculation method, taking an offline road section corresponding to a substation point of the current site in the M offline road sections as a candidate road section of the current site, wherein the current site is a first starting point or any site;

and S302-B12, generating a first transfer route according to the candidate road section of the current stop.

In example 2, offline transfer data is added on the basis of a conventional transfer calculation path to reduce the number of traversal nodes, thereby improving the path planning efficiency. Specifically, according to a preset path calculation method, when traversing the current node, it may be first queried whether there is a road segment whose starting point is the current station in the offline transfer road segment, and if so, connecting the current station with the road segment whose starting point is the current station in the offline transfer road segment as a candidate road segment of the current station. For example, as shown in fig. 7, the M offline sections include 3-4-8 sections and 4-8 sections, and if the current site is site 1, the sub-site included in site 1 includes site 3 and site 4, so that the sections 3-4-8 and 4-8 in the M offline sections can be directly stored in the candidate sections of the current site, and thus the traversal at

sites

3 and 4 becomes less, and a more accurate result is obtained. By analogy, a first transfer route may be generated.

Fig. 8 is a schematic diagram of a transfer route generated by the method according to the embodiment of the present application, as shown in fig. 8, including

transfer routes

1, 2, and 3, where transfer route 1 is a route from line 16 to line 4, takes 54 minutes, and walks for 1.8 km; the heat route 2 is a bus 623-to-subway 16-to-subway 4-line, the time is 1 hour, and the walking is 1.6 kilometers; the heat route 3 is the subway line 16-line-4-line-10-line, takes 1 hour and 1 minute, and walks for 2 kilometers.

The preset path calculation method includes, but is not limited to, BFS, DFS, heuristic a-algorithm, and the like.

In the third mode, when the transfer route is planned according to the preset path calculation method, when the current station is traversed, whether an offline section associated with the current station exists in the M offline sections is firstly inquired, and if the offline section associated with the current station exists in the M offline sections, the offline section corresponding to the substation point of the current station in the M offline sections is used as a candidate section of the current station, so that the traversal times of the substation point of the current station can be reduced, and the planning efficiency of the transfer route is improved.

S303, determining at least one recommended route of the target user according to the N first routes.

In some embodiments, if the N first routes include the first arrival route, the at least one recommended route of the target user may be determined according to the first arrival route, for example, the at least one first arrival route with the highest hot value in the first arrival route is determined as the at least one recommended route of the target user, and the at least one recommended route is sent to the client, so that the client presents the user.

In some embodiments, if the N first paths include both the first arrival route and the first transfer route, at least one route with the highest hot value in the first arrival route and the first transfer route is determined as at least one recommended route of the target user and is sent to the client, so that the client is presented to the user.

In some embodiments, as can be seen from the above description, the road segment heat degree data set further includes a heat degree value corresponding to each offline road segment in the M offline road segments, and based on this, the above step S303 includes the following steps S303-a1 and S303-a 2:

S303-A1, determining the heat value of the first route according to the heat value of the off-line road section corresponding to the first route for each of the N first routes.

For example, the sum of the heat values of the offline sections corresponding to the first route is determined as the heat value of the first route.

For another example, the weighted sum of the heat values of the offline sections corresponding to the first route is determined as the heat value of the first route. For example, the weights corresponding to different road segments are different, and/or the weights corresponding to different indicators are different, for example, the weight of the time consumption indicator of the offline road segment is greater than the weight of the distance indicator of the offline road segment.

For another example, the average value of the heat values of the offline sections corresponding to the first route is determined as the heat value of the first route.

Optionally, the heat value of the first route may also be determined based on the heat value of the offline section corresponding to the first route according to other manners, which is not limited in this application.

S303-A2, determining at least one recommended route of the target user according to the corresponding heat value of each of the N first routes.

For example, the at least one first route with the maximum heat value is cut off into at least one recommended route of the target user.

For another example, if at least one recommended route is 3 recommended routes, 2 direct routes with the largest heat value in the N first routes and one transfer route with the largest heat value are determined as the recommended routes of the target user.

It should be noted that, in the embodiment of the present application, a specific implementation manner of the above-mentioned S303-a2 is not limited, and is specifically selected according to actual needs.

According to the path planning method provided by the embodiment of the application, a first starting point and a first terminal point input by a target user and a road section heat data set are obtained, wherein the road section heat data set comprises M offline road sections, the M offline road sections are generated based on historical route data of the user, and M is a positive integer; determining N first routes with a starting point as a first starting point and an end point as a first end point according to the M offline road sections, wherein N is a positive integer; and determining at least one recommended route of the target user according to the N first routes. Namely, the method and the device determine N first routes with the starting point as the first starting point and the end point as the first end point based on the M offline road sections, and determine at least one recommended route of the target user according to the N first routes, so that all graph nodes are prevented from being traversed, and the route planning efficiency is improved.

In some embodiments, in order to determine that the route recommended to the user is globally optimal, the embodiment of the present application further includes: according to a preset path calculation method, calculating a second direct route with a starting point as a first starting point and an end point as a first end point, wherein the preset path calculation method comprises but is not limited to the following steps: blind search methods such as BFS and DFS, and heuristic search methods such as A.

Based on this, the above S303 includes the following S303-B:

S303-B, determining at least one recommended route of the target user according to the N first routes and the second direct route.

For example, a heat value of each of the N first routes and the second direct routes is determined, and at least one recommended route of the target user is determined according to the heat value of each of the N first routes and the second direct routes. For example, at least one route with the highest calorific value in the N first routes and the N second direct routes is determined as at least one recommended route of the target user.

In some embodiments, before determining at least one recommended route of a target user according to a first direct route and a second direct route of the N first routes, the first direct route and the second direct route need to be detected, and specifically, at least one third direct route which is also a direct route from a destination point to a starting point is selected from the first direct route and the second direct route; and determining at least one recommended route of the target user according to the at least one third direct route.

In some embodiments, in order to determine that the route recommended to the user is globally optimal, the embodiment of the present application further includes: according to a preset path calculation method, a second transfer route is calculated, wherein the starting point is a first starting point, and the end point is a first end point.

Optionally, the preset path calculation method includes, but is not limited to: blind search methods such as BFS and DFS, and heuristic search methods such as A.

Based on this, the above S303 includes the following S303-C:

S303-C, determining at least one recommended route of the target user according to the N first routes and the second transfer route.

For example, a heat value of each of the N first routes and the second transfer routes is determined, and at least one recommended route of the target user is determined according to the heat value of each of the N first routes and the second transfer routes. For example, at least one recommended route of the target user is determined by using the N first routes and the at least one route with the highest heat value in the second transfer route.

Fig. 9 is a schematic flow chart of a path planning method according to an embodiment of the present application, and as shown in fig. 9, the embodiment of the present application includes:

s401, acquiring a first starting point and a first ending point input by a target user and a road section heat data set.

The specific generation process of the road section heat data set refers to the description of S301, and is not described herein again.

S402, if the M offline road sections comprise offline direct road sections, judging whether a first direct route with the starting point as a first starting point and the end point as a first end point exists in the offline direct road sections.

For example, P bus stops which are less than a first preset distance from a first starting point are taken as P candidate starting stations, and Q bus stops which are less than a second preset distance from a first terminal point are taken as Q candidate terminal stations; aiming at the ith candidate starting station in the P candidate starting stations and the jth candidate terminal station in the Q candidate terminal stations, in the offline direct road section, inquiring a first direct route with the starting point as the ith candidate starting station and the terminal point as the jth candidate terminal station, wherein i is a positive integer from 1 to P, and j is a positive integer from 1 to Q. According to the method, each node in the P and the Q is traversed to obtain a first arrival route, wherein the query starting point is the ith candidate starting station and the destination is the jth candidate destination station in the offline direct road section.

If there is a first direct route having a start point as a first start point and an end point as a first end point in the offline direct link, the following step S403 is performed.

If there is no first direct route starting at the first start point and ending at the first end point in the offline direct link, the following step S404 is performed.

And S403, in the off-line direct road section, the inquired start point is a first start point, and a first arrival route with the end point being a first end point is determined as a first route.

S404, according to a preset path calculation method, calculating a second direct route with a starting point as a first starting point and an end point as a first end point.

In some embodiments, a determination is made as to whether the first direct route and the second direct route are destination to start points and direct routes. For example, at least one third direct route which is also a direct route from the terminal point to the starting point is selected from the first direct route and the second direct route, and at least one recommended route of the target user is determined according to the at least one third direct route.

In some embodiments, according to the M offline sections, a first transfer route is generated, wherein the starting point is a first starting point, and the end point is a first end point; and determining the first transfer route as the first route. Specific reference is made to S405 below.

S405, according to a preset path calculation method, when the current station is traversed, whether an offline section corresponding to the substation point of the current station exists in the M offline sections is judged.

If there is an offline section corresponding to the substation point of the current site in the M offline sections, S406 is performed.

If there is no offline section corresponding to the substation point of the current site in the M offline sections, S407 is performed.

S406, taking the off-line road section corresponding to the substation point of the current station in the M off-line road sections as a candidate road section of the current station, generating a first transfer route according to the candidate road section of the current station, and determining the first transfer route as the first route.

S407, calculating a second transfer route with a starting point as a first starting point and an end point as a first end point according to a preset path calculation method.

S408, determining at least one recommended route of the target user according to the first route, the second direct route and the second transfer route.

For example, a heat value corresponding to each of the first route, the second direct route and the second transfer route is determined, and at least one route with the largest heat value is determined as at least one recommended route of the target user.

In some embodiments, bus network data is obtained, including route and stop data, and transfer data. And combining the public transportation road network data, converting at least one route with the maximum heat value into a road network form, namely a bus stop form, filling richer information such as notification, line types and the like, determining the converted route as at least one recommended route, and sending the recommended route to the client so as to display the recommended route by the client. For example, as shown in fig. 10, the generated recommended route includes an express route 1, a transfer route 2, and the like, where the total time of the express route 1 (e.g., 570 buses) is 1 hour and 40 minutes, the total time of the transfer route 1 (e.g., subway 16 line to subway 4 line) is 1 hour and 49 minutes, the total time of the transfer route 1 (e.g., subway 16 line to subway 4 line) is 3.8 kilometers, the total time of the transfer route 2 (e.g., subway 16 line to subway 4 line) is 1 hour and 49 minutes, and the total time of the transfer route 2 (e.g., subway 16 line to subway 4 line) is 3.9 kilometers.

In some embodiments, the application may also modify the road section heat data manually, for example, by increasing the score of an offline road section, or introducing data of passengers entering or leaving the station, adding some hot road sections in time, or adjusting quickly to make the route sequencing more reasonable. Therefore, the road section heat data after modification can be improved, and the road calculation result can be quickly adjusted.

According to the path planning method provided by the embodiment of the application, a first starting point and a first terminal point input by a target user and a road section heat data set are obtained; if the M offline road sections comprise offline direct road sections, judging whether a first direct route with a starting point as a first starting point and an end point as a first end point exists in the offline direct road sections, if so, inquiring the first direct route with the starting point as the first starting point and the end point as the first end point and determining the first direct route as a first route; according to a preset path calculation method, calculating a second direct route with a starting point as a first starting point and an end point as a first end point; according to a preset path calculation method, when a current station is traversed, whether an offline road section corresponding to a substation point of the current station exists in M offline road sections is judged, if yes, the offline road section corresponding to the substation point of the current station in the M offline road sections is used as a candidate road section of the current station, a first transfer route is generated according to the candidate road section of the current station, and the first transfer route is determined to be a first route; calculating a second transfer route with a starting point as a first starting point and an end point as a first end point according to a preset path calculation method; and determining at least one recommended route of the target user according to the first route, the second direct route and the second transfer route, so that the route planning efficiency is improved, and the planned route is ensured to be globally optimal.

The preferred embodiments of the present application have been described in detail with reference to the accompanying drawings, however, the present application is not limited to the details of the above embodiments, and various simple modifications can be made to the technical solution of the present application within the technical idea of the present application, and these simple modifications are all within the protection scope of the present application. For example, the various features described in the foregoing detailed description may be combined in any suitable manner without contradiction, and various combinations that may be possible are not described in this application in order to avoid unnecessary repetition. For example, various embodiments of the present application may be arbitrarily combined with each other, and the same should be considered as the disclosure of the present application as long as the concept of the present application is not violated.

It should also be understood that, in the various method embodiments of the present application, the sequence numbers of the above-mentioned processes do not imply an execution sequence, and the execution sequence of the processes should be determined by their functions and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

Method embodiments of the present application are described in detail above in conjunction with fig. 3-10, and apparatus embodiments of the present application are described in detail below in conjunction with fig. 11-12.

Fig. 11 is a schematic structural diagram of a path planning apparatus according to an embodiment of the present application. The path planning apparatus may be a computing device, or may be a component (e.g., an integrated circuit, a chip, or the like) of the computing device, and the computing device may be a server shown in fig. 1, or may be a terminal device shown in fig. 1.

As shown in fig. 11, the path planning apparatus 10 includes:

an obtaining unit 11, configured to obtain a first start point and a first end point input by a target user, and a road section heat data set, where the road section heat data set includes M offline road sections, the M offline road sections are generated based on historical route data of the user, and M is a positive integer;

a first determining unit 12, configured to determine, according to the M offline road segments, N first routes having a starting point as the first starting point and an end point as the first end point, where N is a positive integer;

a second determining unit 13, configured to determine at least one recommended route of the target user according to the N first routes.

In some embodiments, if the M offline road segments include an offline express road segment, the first determining unit 12 is specifically configured to query, in the offline express road segment, a first express route having a starting point as the first starting point and an end point as the first end point; determining the first direct route as the first route.

In some embodiments, the first determining unit 12 is specifically configured to use P bus stops that are less than a first preset distance from the first start point as P candidate start stations, and use Q bus stops that are less than a second preset distance from the first end point as Q candidate end stations; for the ith candidate starting station in the P candidate starting stations and the jth candidate terminal station in the Q candidate terminal stations, in the offline direct road section, querying a first direct route with a starting point of the ith candidate starting station and a terminal point of the jth candidate terminal station, wherein i is a positive integer from 1 to P, and j is a positive integer from 1 to Q.

In some embodiments, the second determining unit 13 is further configured to calculate, according to a preset path calculation method, a second direct route with a starting point as the first starting point and an end point as the first end point; and determining at least one recommended route of the target user according to the N first routes and the second direct route.

In some embodiments, the second determining unit 13 is specifically configured to select, from the first direct route and the second direct route, at least one third direct route having a direct route from the end point to the start point; and determining at least one recommended route of the target user according to the at least one third direct route.

In some embodiments, the first determining unit 12 is specifically configured to generate, according to the M offline sections, a first transfer route with a starting point as the first starting point and an end point as the first end point; and determining the first transfer route as the first route.

In some embodiments, the first determining unit 12 is specifically configured to, when traversing the current site according to a preset path calculation method, use an offline section corresponding to a sub-point of the current site in the M offline sections as a candidate section of the current site, where the current site is the first starting point or any site; and generating the first transfer route according to the candidate road section of the current station.

In some embodiments, the second determining unit 13 is further configured to calculate a second transfer route with a starting point as the first starting point and an end point as the first end point according to a preset path calculation method; and determining at least one recommended route of the target user according to the N first routes and the second transfer route.

In some embodiments, the section heat data set further includes a heat value corresponding to each of the M offline sections, and the second determining unit 13 is specifically configured to determine, for each of the N first routes, a heat value of the first route according to the heat value of the offline section corresponding to the first route; and determining at least one recommended route of the target user according to the corresponding heat value of each route in the N first routes.

It is to be understood that apparatus embodiments and method embodiments may correspond to one another and that similar descriptions may refer to method embodiments. To avoid repetition, further description is omitted here. Specifically, the apparatus shown in fig. 11 may perform the embodiment of the method described above, and the foregoing and other operations and/or functions of each module in the apparatus are respectively for implementing the embodiment of the method corresponding to the computing device, and are not described herein again for brevity.

The apparatus of the embodiments of the present application is described above in connection with the drawings from the perspective of functional modules. It should be understood that the functional modules may be implemented by hardware, by instructions in software, or by a combination of hardware and software modules. Specifically, the steps of the method embodiments in the present application may be implemented by integrated logic circuits of hardware in a processor and/or instructions in the form of software, and the steps of the method disclosed in conjunction with the embodiments in the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. Alternatively, the software modules may be located in random access memory, flash memory, read only memory, programmable read only memory, electrically erasable programmable memory, registers, and the like, as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps in the above method embodiments in combination with hardware thereof.

Fig. 12 is a schematic block diagram of a computing device provided in an embodiment of the present application, and configured to execute the above method embodiment.

As shown in fig. 12, the computing device 30 may include:

a memory 31 and a processor 32, the memory 31 being arranged to store a computer program 33 and to transfer the program code 33 to the processor 32. In other words, the processor 32 may call and run the computer program 33 from the memory 31 to implement the method in the embodiment of the present application.

For example, the processor 32 may be adapted to perform the above-mentioned method steps according to instructions in the computer program 33.

In some embodiments of the present application, the processor 32 may include, but is not limited to:

general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like.

In some embodiments of the present application, the memory 31 includes, but is not limited to:

volatile memory and/or non-volatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of example, but not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic random access memory (DDR SDRAM), Enhanced Synchronous SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DR RAM).

In some embodiments of the present application, the computer program 33 may be divided into one or more modules, which are stored in the memory 31 and executed by the processor 32 to perform the method of recording pages provided herein. The one or more modules may be a series of computer program instruction segments capable of performing certain functions, the instruction segments describing the execution of the computer program 33 in the computing device.

As shown in fig. 12, the computing device 30 may further include:

a transceiver 34, the transceiver 34 being connectable to the processor 32 or the memory 31.

The processor 32 may control the transceiver 34 to communicate with other devices, and specifically, may transmit information or data to the other devices or receive information or data transmitted by the other devices. The transceiver 34 may include a transmitter and a receiver. The transceiver 34 may further include one or more antennas.

It should be understood that the various components in the computing device 30 are connected by a bus system that includes a power bus, a control bus, and a status signal bus in addition to a data bus.

According to an aspect of the present application, there is provided a computer storage medium having a computer program stored thereon, which, when executed by a computer, enables the computer to perform the method of the above-described method embodiments. In other words, the present application also provides a computer program product containing instructions, which when executed by a computer, cause the computer to execute the method of the above method embodiments.

According to another aspect of the application, a computer program product or computer program is provided, comprising computer instructions stored in a computer readable storage medium. The computer instructions are read by a processor of the computing device from the computer-readable storage medium, and the processor executes the computer instructions to cause the computing device to perform the method of the above-described method embodiment.

In other words, when implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The procedures or functions described in accordance with the embodiments of the present application occur, in whole or in part, when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a Digital Video Disk (DVD)), or a semiconductor medium (e.g., a Solid State Disk (SSD)), among others.

Those of ordinary skill in the art will appreciate that the various illustrative modules and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the module is merely a logical division, and other divisions may be realized in practice, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.

Modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. For example, functional modules in the embodiments of the present application may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of path planning, comprising:

2. The method of claim 1, wherein the M offline sections comprise at least one of offline express sections and offline transfer sections.

3. The method according to claim 2, wherein if the M offline sections include an offline express section, the determining N first routes having a starting point as the first starting point and an ending point as the first ending point according to the M offline sections includes:

in the offline through road section, inquiring a first straight-through route with a starting point as the first starting point and an end point as the first end point;

determining the first direct route as the first route.

4. The method according to claim 3, wherein the querying a first arrival route with a starting point being the first starting point and an ending point being the first ending point in the offline direct road segment comprises:

taking P bus stops which are less than a first preset distance away from the first starting point as P candidate starting stations, and taking Q bus stops which are less than a second preset distance away from the first terminal point as Q candidate terminal stations;

for the ith candidate starting station in the P candidate starting stations and the jth candidate terminal station in the Q candidate terminal stations, in the offline direct road section, querying a first direct route with a starting point of the ith candidate starting station and a terminal point of the jth candidate terminal station, wherein i is a positive integer from 1 to P, and j is a positive integer from 1 to Q.

5. The method of claim 3, further comprising:

according to a preset path calculation method, calculating a second direct route with a starting point as the first starting point and an end point as the first end point;

the determining at least one recommended route of the target user according to the N first routes includes:

and determining at least one recommended route of the target user according to the N first routes and the second direct route.

6. The method of claim 5, wherein determining at least one recommended route for the target user based on the N first routes and the second direct routes comprises:

selecting at least one third direct route from the first direct route and the second direct route, wherein the destination to the starting point is the direct route;

and determining at least one recommended route of the target user according to the at least one third direct route.

7. The method according to any one of claims 2-6, wherein the determining, according to the M offline sections, the N first routes having a starting point as the first starting point and an ending point as the first ending point comprises:

generating a first transfer route with a starting point as the first starting point and a terminal point as the first terminal point according to the M offline sections;

and determining the first transfer route as the first route.

8. The method according to claim 7, wherein the generating a first transfer route with a starting point as the first starting point and an end point as the first end point according to the M offline sections comprises:

according to a preset path calculation method, when a current site is traversed, an offline road section corresponding to a sub-station point of the current site in the M offline road sections is used as a candidate road section of the current site, and the current site is the first starting point or any site;

and generating the first transfer route according to the candidate road section of the current station.

9. The method of claim 7, further comprising:

according to a preset path calculation method, calculating a second transfer route with a starting point as the first starting point and an end point as the first end point;

and determining at least one recommended route of the target user according to the N first routes and the second transfer route.

10. The method according to any one of claims 1 to 6, wherein the M offline sections are sections formed by multi-path splitting of a plurality of offline routes based on a site, and the plurality of offline routes are a plurality of routes generated based on a starting point and an ending point in the historical route data of the user.

11. The method of claim 10, wherein the starting point and the ending point in the historical route data of the user are visited by the user more than a first number of times.

12. The method of claim 10, wherein the number of transfers for each of the M offline sections is less than a second value.

13. The method according to any one of claims 1-6, wherein the segment heat data set further comprises a heat value corresponding to each of the M offline segments, and wherein determining at least one recommended route for the target user according to the N first routes comprises:

for each of the N first routes, determining a heat value of the first route according to a heat value of an offline section corresponding to the first route;

and determining at least one recommended route of the target user according to the corresponding heat value of each route in the N first routes.

14. The method of claim 13, wherein the heat value of the offline section is determined based on at least one of a number of times the offline section is accessed, a distance of the offline section, a total elapsed time corresponding to the offline section, a riding time corresponding to the offline section, a walking time corresponding to the offline section, and a number of transfers corresponding to the offline section.

15. A path planning apparatus, comprising:

16. A computing device, comprising: a memory, a processor;

the memory for storing a computer program;

the processor for executing the computer program to implement the method of any one of the preceding claims 1 to 14.

17. A computer-readable storage medium having computer-executable instructions stored thereon, which when executed by a processor, are configured to implement the method of any one of claims 1 to 14.